Elite AI hackers aren’t born. They’re trained.
Elite AI hackers aren’t born. They’re trained.
Promptfoo is a capable open-source tool for red-teaming models but it stops at the model layer, needs a person to run it, and leaves the running application untouched. Novee tests what attackers actually exploit, and proves every finding.
Model-layer testing is useful, but it leaves most of your attack surface untested, including the flaws attackers actually exploit.
Scoped to the model layer.
A human has to drive it.
No proprietary offensive AI.
Blind to business logic and chained attacks.
Stops at model output flags.
Securing applications with AI features is one important part of an entire penetration testing suite. Novee tests the entire AI application, model included, and then proves validity of what it finds. On top of that, it extends coverage into the other attack surfaces that matter for your business.
Coverage across the full attack surface.
Finds the flaws that matter.
A proprietary offensive AI stack.
Fully autonomous and continuous.
Validation built for zero false positives.
A closed loop to a verified fix.
| Capability | Novee AI Pentesting | Promptfoo |
|---|---|---|
| Coverage | Web apps, APIs, mobile apps, and AI agents/LLMs across your external footprint, tested black box from a domain name. |
AI/LLM model layer only. |
| Application context and depth | Builds an Asset Intelligence Model before testing, mapping roles, workflows, APIs, and business logic, so it finds the IDOR, auth bypass, and chained exploits that live in how the app actually works. Context compounds every cycle. |
Tests model behavior in isolation. No application context, and none that compounds across runs. |
| Offensive model and harness | Proprietary harness and proprietary offensive reasoning model, post-trained on real attacker tradecraft and orchestrated with leading frontier models selected per task. |
Open-source framework. No proprietary offensive model, harness, or training of its own. |
| Autonomous, continuous testing | Fully autonomous. Runs on demand or automatically when code ships via CI/CD. No scheduling, tokens, or human intervention. Coverage deepens each cycle. |
Requires human configuration. Runs only when a person triggers it. |
| Validation architecture | Three independent agents (a finder, a validator, and a blind re-validator with no context from the first two) plus deterministic checks where possible. If any stage fails, the finding is never reported. |
Model-output flags only. No independent validation process or deterministic confirmation described. |
| Closed-loop remediation & retesting | Remediation tailored to your WAF, backend, and codebase rather than generic OWASP pointers. Automatic retesting confirms the fix held and flags new risk the change introduced. |
No stack-specific remediation or retesting. |
| Workflow & integrations | Native CI/CD plus developer-workflow integrations (GitHub, Jira). Connected to CI/CD, fixes drop to the code level, aligned to your codebase. |
CI/CD for model testing only. No broader developer-workflow integrations. |
| Pricing | Predictable per-asset pricing. Depth and frequency don’t increase cost. |
Open-source and free; paid probes per month. |